Transform camera pose to world interpretation
Hello,
I read the tutorial on transforms. I followed the step Checking the results, by running
$ rosrun tf tf_echo /world /turtle1
it should show the pose of the first turtle. I have a very similar situation but for ORB-SLAM. Following someones code, I run
$ rosrun tf tf_echo /world /camera_pose
and receive
- Translation [-0.8, 0.66, -0.04]
Rotation in Quaternion [ 0.2, -0.3, -0.2, 0.2]
in RPY radian: [0.071, -0.032, -0.34]
in RPY degree [0.4, -25.09, -3.2]
How do I interpret this? Does it mean that camera_pose is at [-0.8, 0.66, -0.04] global coordinates or that its at translation T and rotation R from the original world coordinate [0,0,0]? If the latter is the case, then how do I get the pose of the camera in world coordinates? I need it so I can compare it to ground truth.
A transformation is the inverse of a pose. Think of it as the transformation needed to convert a point represented in the first frame to one represented in the second frame. It is not the pose of the camera in the world frame
How do I get the pose of the camera in the world frame?
You can lookup the transformation from the camera frame to the world frame (because this is the inverse of the TF from the world frame to the camera frame)
Do you mean this http://www.optique-ingenieur.org/en/c... ? How can I even check if my transformations are correct?
You'll have to have an independent source of measurement in order to check they're correct fully. But you should be able to get a good idea they roughly correct by looking at the translation values.
I looked at the ground truth data of the rosbag that I was trying to get the camera_pose. I see that the ground truth is shown by tx, ty, tz, qx, qy, qz, qw. Does it mean that the ground truth is shown by calculating the translation and rotation from the world coordinate?
That really depends what sensors and topics are in your bag file. Is it a pose topic or the TF topic? And what is it's frame_id?
https://vision.in.tum.de/rgbd/dataset... This is the ground truth data. They dont mention topic of it, but when I looked at the tf frames.pdf, I saw there was a World -> Kinect frame which was the highest up in the graph, so I assumed it may be that.